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Analyzing social media via event facets

Published: 29 October 2012 Publication History

Abstract

Microblog is a prominent information platform for sharing experiences, discussing current events, and exchanging ideas. Many events are first reported in social media, and increasing amounts of rich-media content are associated with the posts, making them more credible and attractive. We design a rich-media analysis system to address the important challenge of sensing and exploring events from social media in real-time. The system includes a novel bilateral correspondence topic model to extract representative content and meaningful facets about events over time. It also includes a digital magazine that anchors user interactions with event facets. We demonstrate several examples from more than 4 million rich media microblogs, showing the effectiveness of key content extraction and natrual interactions with facets.

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References

[1]
K. Barnard, P. Duygulu, D. Forsyth, N. De Freitas, D. Blei, and M. Jordan. Matching words and pictures. The Journal of Machine Learning Research, 3:1107--1135, 2003.
[2]
M. Wang, R. Hong, G. Li, Z. Zha, S. Yan, and T. Chua. Event driven web video summarization by tag localization and key-shot identification. Multimedia, IEEE Transactions on, (99):1--1, 2011.
[3]
J. Weng and B. Lee. Event detection in twitter. In Fifth International AAAI Conference on Weblogs and Social Media, 2011.

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cover image ACM Conferences
MM '12: Proceedings of the 20th ACM international conference on Multimedia
October 2012
1584 pages
ISBN:9781450310895
DOI:10.1145/2393347

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 October 2012

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Author Tags

  1. BC-LDA
  2. automatic layout
  3. multi-modal microblog

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MM '12
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MM '12: ACM Multimedia Conference
October 29 - November 2, 2012
Nara, Japan

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